Modelling of Grass Pollen Interannual Variability in the UK: A Mechanistic Approach

Background
Seasonal pollen integral (SPIn) – the integral over time of pollen concentration - is considered an important parameter in aerobiological studies. It is mainly used to quantify the severity of pollen seasons as well as in numerical models to simulate pollen emissions and concentrations. According to the recent studies the SPIn interannual variability is modelled using a statistical approach by analysing 10-20 years of pollen and meteorological observations at the specific region.
Methods
This study is based on a mechanistic approach which describes grass growth by variation of meteorological parameters in the UK: air temperature, precipitation, shortwave radiation, as well as CO2. Our approach suggests that grass growth correlates with the grass SPIn interannual variability. Six pollen observation sites across the UK have been chosen for this study: Worcester, Leicester, Cardiff, Plymouth, Isle of Wight and Invergowrie. The pollen observation data cover a 21-year period (1995-2015). The meteorological data, provided by the UK Met Office, are gridded data with 5 km horizontal resolution over the UK. The mechanistic approach will be tested for the selected sites and then applied to the grid.
Results
Analysis of the grass SPIn interannual variability showed the highest SPIn variation at Worcester (from 2908 pollen*day/m3 in 1995 to 10856 pollen*day/m3 in 2006) and Isle of Wight (from 1423 pollen*day/m3 in 1999 to 6815 pollen*day/m3 in 2013) among the considered stations. This could be explained by high variation of local pollen sources at the Worcester site and atmospheric transport from the South to Isle of Wight.
Conclusions
The grass SPIn analysis did not show correlation between the selected stations during the period studied. The new approach also has the practical application that it can be used directly to estimate local grass pollen productivity in the UK for a better estimation of the severity of the grass pollen season.